MAE {DiceEval}

Mean Absolute Error

Description

The mean of absolute errors between real values and predictions.

Usage

MAE(Y, Ypred)

Arguments

Y

a real vector with the values of the output

Ypred

a real vector with the predicted values at the same inputs

Value

a real which represents the mean of the absolute errors between the real and the predicted values:

MAE = \frac{1}{n} \sum_{i=1}^{n} | Y \left( x_{i}\right)-\hat{Y} \left( x_{i}\right)|

where x_{i} denotes the points of the experimental design, Y the output of the computer code and \hat{Y} the fitted model.

Author(s)

D. Dupuy

See Also

other quality criteia as RMSE and RMA.

Examples

X	<- seq(-1,1,0.1)
Y	<- 3*X + rnorm(length(X),0,0.5)
Ypred	<- 3*X
MAE(Y,Ypred)